Publication

Test-time adaptation for 6D pose tracking

Related publications (41)

Bridging the Gap between Detection and Tracking for 3D Human Motion Recovery

The aim of this thesis is to build a system able to automatically and robustly track human motion in 3–D starting from monocular input. To this end two approaches are introduced, which tackle two different types of motion: The first is useful to analyze ac ...

EPFL2010

Learning Pose Invariant and Covariant Classifiers from Image Sequences

Mustafa Özuysal

Object tracking and detection over a wide range of viewpoints is a long-standing problem in Computer Vision. Despite significant advance in wide-baseline sparse interest point matching and development of robust dense feature models, it remains a largely op ...

EPFL2010

Video-Based Camera Tracking Using Rotation-Discriminative Template Matching

Touradj Ebrahimi

This paper presents a video-based camera tracker that combines marker-based and feature point-based cues in a particle filter framework. The framework relies on their complementary performance. Marker-based trackers can robustly recover camera position and ...

Springer2009

Observable Subspaces for 3D Human Motion Recovery

Pascal Fua, Mathieu Salzmann, Andrea Fossati

The articulated body models used to represent human motion typically have many degrees of freedom, usually expressed as joint angles that are highly correlated. The true range of motion can therefore be represented by latent variables that span a low-dimen ...

Ieee Service Center, 445 Hoes Lane, Po Box 1331, Piscataway, Nj 08855-1331 Usa2009

Multi-view video segmentation and tracking for video surveillance

Touradj Ebrahimi, Frédéric Dufaux, Gelareh Mohammadi, Thien Ha Minh

Tracking moving objects is a critical step for smart video surveillance systems. Despite the complexity increase, multiple camera systems exhibit the undoubted advantages of covering wide areas and handling the occurrence of occlusions by exploiting the di ...

2009

Geometry-aware analysis of high-dimensional visual information sets

Effrosyni Kokiopoulou

Over the past few decades we have been experiencing a data explosion; massive amounts of data are increasingly collected and multimedia databases, such as YouTube and Flickr, are rapidly expanding. At the same time rapid technological advancements in mobil ...

EPFL2009

Multi-camera multi-person 3d space tracking with mcmc in surveillance scenarios

Jean-Marc Odobez

We present an algorithm for the tracking of a variable number of 3D persons in a multi-camera setting with partial field-of-view overlap. The multi-object tracking problem is posed in a Bayesian framework and relies on a joint multi-object state space with ...

2008

Fast multi-view face tracking with pose estimation

Jean-Philippe Thiran, Javier Cruz Mota, Julien Meynet

In this paper, a fast and an effective multi-view face tracking algorithm with head pose estimation is introduced. For modeling the face pose we employ a tree of boosted classiﬁers built using either Haar-like ﬁlters or Gauss ﬁlters. A ﬁrst classiﬁer extra ...

2008

Fast multi-view face tracking with pose estimation

Jean-Philippe Thiran, Javier Cruz Mota, Julien Meynet

In this paper, a fast and effective multi-view face tracking algorithm with head pose estimation is introduced. For modeling the face pose, we employ a tree of boosted classifiers built using either Haar-like filters or Gauss filters. A first classifier ex ...

2008

Advances in top-down and bottom-up approaches to video-based camera tracking

David Marimon Sanjuan

Video-based camera tracking consists in trailing the three dimensional pose followed by a mobile camera using video as sole input. In order to estimate the pose of a camera with respect to a real scene, one or more three dimensional references are needed. ...

EPFL2007

Graph Chatbot

Chat with Graph Search

Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.

DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.